Innovations in Computer Vision and Data Classification: From Pandemic Data Analysis to Environmental and Health Monitoring

This book delves into the dynamic realm of data classification, focusing on its real-world applications. Through an insightful journey, readers are introduced to the practical applications of reconfigurable hardware, machine learning, computer vision, and neuromorphic circuit design across diverse domains. The author explores topics such as the role of Field-Programmable Gate Arrays (FPGAs) in expediting pandemic data analysis and the transformative impact of computer vision on healthcare. Additionally, the book delves into environmental data classification, energy-efficient solutions for deep neural network applications, and real-time performance analysis of energy conversion algorithms. With the author’s guidance, readers are led through practical implementations, ensuring a comprehensive grasp of each subject matter. Whether a seasoned researcher, engineer, or student, this book equips readers with the tools to make data-driven decisions, optimize systems, and innovate solutions across various fields, from healthcare to environmental monitoring.

Dr. Arfan Ghani is working as an Associate Professor in Computer Engineering at the American University of Ras al Khaimah, UAE. He gained academic qualifications and experience working in UK institutions including Ulster, Coventry, and Newcastle. His industrial research and development experience includes working at Intel Research, University of Cambridge and Vitesse Semiconductors Denmark. Arfan has over 18 years of applied research experience. He has published in leading journals and conferences and secured substantial collaborative funding from EPSRC, EU, Innovate UK, the Royal Academy of Engineering, and the German Aerospace Centre. He serves as an Associate Editor of Elsevier Neurocomputing, Guest Editor, Technical Programme Committee member for several IEEE/IET conferences and a keynote speaker. He has received several awards including the best paper and winner from the European Neural Network Society in 2007. Arfan is a member of IET, a Chartered Engineer (CEng) and a Fellowof the Higher Education Academy in the UK.